The present disclosure is directed generally to the reconstruction of tomographic images and, more specifically, to approaches for reconstructing tomographic images using iterative reconstruction.
Non-invasive imaging technologies allow images of the internal structures of a patient or object to be obtained without performing an invasive procedure on the patient or object. In particular, technologies such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and single positron emission computed tomography (SPECT) use various physical principles to acquire image data and to construct tomographic images (e.g., three-dimensional representations of the interior of the human body or of other imaged structures).
The reconstruction of tomographic images may be a laborious and time-consuming process. For example, certain reconstruction processes attempt to utilize an approach where the image reconstruction processes are iterated until some degree of convergence based on some image quality criteria is achieved. Certain of these iterative reconstruction approaches utilize simultaneous update methods that are suitable for parallel implementation or processing. However, these types of iterative approaches may also be subject to slow convergence speed for various high frequency image features. Further, such iterative approaches may be very processor-intensive, requiring large amounts of processor power to implement effectively.